Search Results
Description and validation of the ice-sheet model Yelmo (version 1.0)
We describe the physics and features of the ice-sheet model Yelmo, an open-source project intended for collaborative development. Yelmo is a thermomechanical model, solving for the coupled velocity and temperature solutions of an ice sheet simultaneously. The ice dynamics are currently treated via a “hybrid” approach combining the shallow-ice and shallow-shelf/shelfy-stream approximations, which makes Yelmo an apt choice for studying a wide variety of problems. Yelmo's main innovations lie in its flexible and user-friendly infrastructure, which promotes portability and facilitates long-term development. In particular, all physics subroutines have been designed to be self-contained, so that they can be easily ported from Yelmo to other models, or easily replaced by improved or alternate methods in the future. Furthermore, hard-coded model choices are eschewed, replaced instead with convenient parameter options that allow the model to be adapted easily to different contexts. We show results for different ice-sheet benchmark tests, and we illustrate Yelmo's performance for the Antarctic ice sheet.
RADAR: Building a FAIR and Community Tailored Research Data Repository
The research data repository RADAR is designed to support the secure management, archiving, publication and dissemination of digital research data from completed scientific studies and projects. Developed as a collaborative project funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (2013-2016), the system is operated by FIZ Karlsruhe - Leibniz Institute for Information Infrastructure - and currently serves as a generic cloud service for about 20 universities and non-university research institutions. Since its launch, RADAR has witnessed significant changes in the landscape of research data repositories and the evolving needs of researchers, research communities and institutions. In our presentation within the “Enabling RDM” Track, we will show how RADAR is responding to these dynamic changes. In order to create a sufficiently large user base for the sustainable operation of the system, we have moved RADAR away from its previous single focus on a discipline-agnostic cloud service and towards a demand-driven functional optimisation. In 2021, we introduced an additional operating model for institutions (RADAR Local), where we operate a separate RADAR instance locally at the institution site exclusively using the institutional IT-infrastructure. In 2022 we opened up RADAR to new target groups with community-specific service offerings, in particular in the context of the National Research Data Infrastructure (NFDI). Beside the expansion of the functional scope, our ongoing development work focuses also on strengthening the system's support for the FAIR principles [1] and the concepts of FAIR Digital Objects (FDO) [2] and Schema.org. Our presentation will outline recent RADAR developments and achievements as well as future plans thus providing solutions and synergy potential for the scientific community and for other service providers.
What metrics best reflect the energy and carbon intensity of cities? Insights from theory and modeling of 20 US cities
Three broad approaches have emerged for energy and greenhouse gas (GHG) accounting for individual cities: (a) purely in-boundary source-based accounting (IB); (b) community-wide infrastructure GHG emissions footprinting (CIF) incorporating life cycle GHGs (in-boundary plus trans-boundary) of key infrastructures providing water, energy, food, shelter, mobility-connectivity, waste management/sanitation and public amenities to support community-wide activities in cities - all resident, visitor, commercial and industrial activities; and (c) consumption-based GHG emissions footprints (CBF) incorporating life cycle GHGs associated with activities of a sub-set of the community - its final consumption sector dominated by resident households. The latter two activity-based accounts are recommended in recent GHG reporting standards, to provide production-dominated and consumption perspectives of cities, respectively. Little is known, however, on how to normalize and report the different GHG numbers that arise for the same city. We propose that CIF and IB, since they incorporate production, are best reported per unit GDP, while CBF is best reported per capita. Analysis of input-output models of 20 US cities shows that GHGCIF/GDP is well suited to represent differences in urban energy intensity features across cities, while GHGCBF/capita best represents variation in expenditures across cities. These results advance our understanding of the methods and metrics used to represent the energy and GHG performance of cities.
From Floppy Disks to 5-Star LOD: FAIR Research Infrastructure for NFDI4Culture
NFDI4Culture is establishing an infrastructure for research data on material and immaterial cultural heritage in the context of the German National Research Data Infrastructure (NFDI) in compliance with the FAIR principles. The NFDI4Culture Knowledge Graph is developed and integrated with the Culture Information Portal to aggregate diverse and isolated data from the culture research landscape and thereby increase the discoverability, interoperability and reusability of cultural heritage data. This paper presents the research data management strategy in the long-term project NFDI4Culture, which combines a CMS and a Knowledge Graph-based infrastructure to enable an intuitive and meaningful interaction with research resources in the cultural heritage domain.